A decision-support system for transportation and logistics

Our machine-learning systems are helping decision-making for transport authorities and commuters resulting in greener, more efficient and more sustainable transport and logistics.

Partnering with Peel Ports Group, Merseyrail, Liverpool City Region Combined Authority, Merseytravel, the six local authorities and The University of Liverpool, our real-time monitoring of road, rail and maritime transport has:

  • Reduced costs up to 23%, emissions up to 19%, and accidents estimated at 10% in the port/maritime industry.
  • Improved rail performance and passenger experience at four of Merseyrail’s busiest stations (~24 million passengers annually).
  • Supported active travel options (walking and cycling) in the Liverpool City Region by providing data/analysis to the public and operators. Inputs from the system are underpinning the upgrade of 57.5km green cycling/walking routes to reduce greenhouse gas emissions by an up to 334 tonnes.

"LJMU has helped us with improving our day-to-day operations. At Liverpool South Parkway our system is providing passengers with rapid, real-time information on network disruption. It had served about 200,000 passengers within the first two months of operation, receiving a score of 10/10 from staff who used it and 8/10 from passengers." - Station Compliance Manager, Merseyrail

LJMU Academics

Professor Thanh Nguyen

Professor Zaili Yang

Dr Zhuohua Qu

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